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Changelog

Source: NEWS.md

model.parameters.pipeline 0.1.0

Initial Release (2026-01-08)

This is the first release of the Model Parameters Pipeline package, implementing transformations according to the Model Parameters specification developed by Big Life Lab.

Features

  • Core Pipeline Functionality: Sequential data transformation pipeline supporting multiple transformation steps
  • Transformation Steps:
    • center: Centers variables by subtracting a specified value
    • dummy: Creates dummy variables for categorical values
    • interaction: Creates interaction terms by multiplying variables
    • rcs: Applies restricted cubic spline transformations
    • logistic-regression: Applies logistic regression with coefficients
  • Flexible Input: Support for both file paths and data frames as inputs
  • Performance Optimization: Ability to reuse model objects for repeated transformations with different data
  • Model Parameters Specification: Full compatibility with Big Life Lab’s Model Parameters specification used by HTNPoRT, DemPoRT, CVDPoRT, and MPoRT models

Documentation

  • Comprehensive README with usage examples and file structure documentation
  • Function documentation for all exported functions
  • HTNPoRT model example demonstrating real-world usage
  • Guide for adding new transformation steps (ADDING_NEW_STEP.md)

Testing

  • Test suite using testthat framework
  • Tests for all transformation steps
  • Integration tests for complete pipeline execution